An image may be segmented into separate regions, for such purposes as computer vision, image processing and computer graphics applications. Semi-automatic segmentation, in general, relies on some form of user input to segment an image into two or more separate regions, with each of these regions corresponding to a particular object (or the background, which itself may be considered an object).
For example, a user may introduce input to semi-automatic segmentation application by “scribbling” on each object of interest in an image for purposes of marking the object and identifying a small number of pixels that are contained within the object. A bounding box is another way in which a user may mark an object of interest and identify a small number of pixels that are contained within the object.
Semi-automatic segmentation may be used, for example, in the arena of image editing tools, such as in graphic arts and elsewhere, in which objects are extracted from images. The more minimal the user input, the faster the graphic artist is able to complete the underlying task. Semi-automatic segmentation may also be used in medical imaging, which allows a physician to, for example, quickly and accurately segment a particular organ or tumor, thereby allowing image-guided radiation therapy planning, among many other possible applications.